package two.newdawn.API.noise;

import java.util.Random;

/*
 * A speed-improved simplex noise algorithm for 2D, 3D and 4D in Java.
 *
 * Based on example code by Stefan Gustavson (stegu@itn.liu.se). Optimisations
 * by Peter Eastman (peastman@drizzle.stanford.edu). Better rank ordering method
 * by Stefan Gustavson in 2012.
 *
 * This could be speeded up even further, but it's useful as it is.
 *
 * Version 2012-03-09
 *
 * This code was placed in the public domain by its original author, Stefan
 * Gustavson. You may use it as you see fit, but attribution is appreciated.
 *
 */
public class SimplexNoise {  // Simplex noise in 2D, 3D and 4D

  private static final Grad grad3[] = {new Grad(1, 1, 0), new Grad(-1, 1, 0), new Grad(1, -1, 0), new Grad(-1, -1, 0),
    new Grad(1, 0, 1), new Grad(-1, 0, 1), new Grad(1, 0, -1), new Grad(-1, 0, -1),
    new Grad(0, 1, 1), new Grad(0, -1, 1), new Grad(0, 1, -1), new Grad(0, -1, -1)};
  private static final Grad grad4[] = {new Grad(0, 1, 1, 1), new Grad(0, 1, 1, -1), new Grad(0, 1, -1, 1), new Grad(0, 1, -1, -1),
    new Grad(0, -1, 1, 1), new Grad(0, -1, 1, -1), new Grad(0, -1, -1, 1), new Grad(0, -1, -1, -1),
    new Grad(1, 0, 1, 1), new Grad(1, 0, 1, -1), new Grad(1, 0, -1, 1), new Grad(1, 0, -1, -1),
    new Grad(-1, 0, 1, 1), new Grad(-1, 0, 1, -1), new Grad(-1, 0, -1, 1), new Grad(-1, 0, -1, -1),
    new Grad(1, 1, 0, 1), new Grad(1, 1, 0, -1), new Grad(1, -1, 0, 1), new Grad(1, -1, 0, -1),
    new Grad(-1, 1, 0, 1), new Grad(-1, 1, 0, -1), new Grad(-1, -1, 0, 1), new Grad(-1, -1, 0, -1),
    new Grad(1, 1, 1, 0), new Grad(1, 1, -1, 0), new Grad(1, -1, 1, 0), new Grad(1, -1, -1, 0),
    new Grad(-1, 1, 1, 0), new Grad(-1, 1, -1, 0), new Grad(-1, -1, 1, 0), new Grad(-1, -1, -1, 0)};
  // Skewing and unskewing factors for 2, 3, and 4 dimensions
  private static final double F2 = 0.5 * (Math.sqrt(3.0) - 1.0);
  private static final double G2 = (3.0 - Math.sqrt(3.0)) / 6.0;
  private static final double F3 = 1.0 / 3.0;
  private static final double G3 = 1.0 / 6.0;
  private static final double F4 = (Math.sqrt(5.0) - 1.0) / 4.0;
  private static final double G4 = (5.0 - Math.sqrt(5.0)) / 20.0;

  /* Static helper functions */
  private static int fastfloor(double x) {
    int xi = (int) x;
    return x < xi ? xi - 1 : xi;
  }

  private static double dot(Grad g, double x, double y) {
    return g.x * x + g.y * y;
  }

  private static double dot(Grad g, double x, double y, double z) {
    return g.x * x + g.y * y + g.z * z;
  }

  private static double dot(Grad g, double x, double y, double z, double w) {
    return g.x * x + g.y * y + g.z * z + g.w * w;
  }
  /**
   * Class members
   */
  protected final short[] doubledPermutationTable;
  protected final short[] variatedPermutationTable;
  protected final Random random;

  /**
   * Generate a new noise field using the given random generator.
   * 
   * @param random the random generator to use to initialize this field.
   */
  public SimplexNoise(final Random random) {
    final byte[] bytes = new byte[1024];
    this.random = random;
    random.nextBytes(bytes);
    doubledPermutationTable = new short[bytes.length * 2];
    variatedPermutationTable = new short[doubledPermutationTable.length];
    for (int i = 0; i < bytes.length; ++i) {
      final short value = (short) (bytes[i] & 0xFF);
      doubledPermutationTable[i] = value;
      variatedPermutationTable[i] = (short) (value % 12);
    }
    System.arraycopy(doubledPermutationTable, 0, doubledPermutationTable, bytes.length, bytes.length);
    System.arraycopy(variatedPermutationTable, 0, variatedPermutationTable, bytes.length, bytes.length);
  }

  /**
   * Returns the random that was used to initialize this noise field.
   *
   * @return the random that was used to initialize this noise field.
   */
  public Random getRandom() {
    return random;
  }

  /**
   * Generates a new 2D noise stretcher based on this noise.
   *
   * @param stretchX the stretch value for x-coordinates.
   * @param stretchZ the stretch value for z-coordinates.
   * @param offsetX an offset added to the x-coordinate, which should be initialized with a random value like random.nextDouble().
   * @param offsetZ an offset added to the z-coordinate, which should be initialized with a random value like random.nextDouble().
   * @return a 2D NoiseStrech using this noise.
   */
  public NoiseStretch generateNoiseStretcher(double stretchX, double stretchZ, double offsetX, double offsetZ) {
    return new NoiseStretch(this, stretchX, stretchZ, offsetX, offsetZ);
  }

  /**
   * Generates a new 3D noise stretcher based on this noise.
   *
   * @param noise the base noise to use.
   * @param stretchX the stretch value for x-coordinates.
   * @param stretchY the stretch value for y-coordinates.
   * @param stretchZ the stretch value for z-coordinates.
   * @param offsetX an offset added to the x-coordinate, which should be initialized with a random value like random.nextDouble().
   * @param offsetY an offset added to the y-coordinate, which should be initialized with a random value like random.nextDouble().
   * @param offsetZ an offset added to the z-coordinate, which should be initialized with a random value like random.nextDouble().
   * @return a 3D NoiseStrech using this noise.
   */
  public NoiseStretch generateNoiseStretcher(double stretchX, double stretchY, double stretchZ, double offsetX, double offsetY, double offsetZ) {
    return new NoiseStretch(this, stretchX, stretchY, stretchZ, offsetX, offsetY, offsetZ);
  }
  // 2D simplex noise

  public double noise(double xin, double yin) {
    // Skew the input space to determine which simplex cell we're in
    final double s = (xin + yin) * F2; // Hairy factor for 2D
    final int i = fastfloor(xin + s);
    final int j = fastfloor(yin + s);
    final double t = ((double) (i + j)) * G2;
    final double X0 = (double) i - t; // Unskew the cell origin back to (x,y) space
    final double Y0 = (double) j - t;
    final double x0 = xin - X0; // The x,y distances from the cell origin
    final double y0 = yin - Y0;
    // For the 2D case, the simplex shape is an equilateral triangle.
    // Determine which simplex we are in.
    final int i1, j1; // Offsets for second (middle) corner of simplex in (i,j) coords
    if (x0 > y0) {
      i1 = 1;
      j1 = 0;
    } else { // lower triangle, XY order: (0,0)->(1,0)->(1,1)
      i1 = 0;
      j1 = 1;
    }      // upper triangle, YX order: (0,0)->(0,1)->(1,1)
    // A step of (1,0) in (i,j) means a step of (1-c,-c) in (x,y), and
    // a step of (0,1) in (i,j) means a step of (-c,1-c) in (x,y), where
    // c = (3-sqrt(3))/6
    final double x1 = x0 - (double) i1 + G2; // Offsets for middle corner in (x,y) unskewed coords
    final double y1 = y0 - (double) j1 + G2;
    final double x2 = x0 - 1.0 + 2.0 * G2; // Offsets for last corner in (x,y) unskewed coords
    final double y2 = y0 - 1.0 + 2.0 * G2;
    // Work out the hashed gradient indices of the three simplex corners
    final int ii = i & 1023;
    final int jj = j & 1023;
    final int gi0 = variatedPermutationTable[ii + doubledPermutationTable[jj]];
    final int gi1 = variatedPermutationTable[ii + i1 + doubledPermutationTable[jj + j1]];
    final int gi2 = variatedPermutationTable[ii + 1 + doubledPermutationTable[jj + 1]];
    final double n0, n1, n2; // Noise contributions from the three corners
    // Calculate the contribution from the three corners
    double t0 = 0.5 - x0 * x0 - y0 * y0;
    if (t0 < 0) {
      n0 = 0.0;
    } else {
      t0 *= t0;
      n0 = t0 * t0 * dot(grad3[gi0], x0, y0);  // (x,y) of grad3 used for 2D gradient
    }
    double t1 = 0.5 - x1 * x1 - y1 * y1;
    if (t1 < 0) {
      n1 = 0.0;
    } else {
      t1 *= t1;
      n1 = t1 * t1 * dot(grad3[gi1], x1, y1);
    }
    double t2 = 0.5 - x2 * x2 - y2 * y2;
    if (t2 < 0) {
      n2 = 0.0;
    } else {
      t2 *= t2;
      n2 = t2 * t2 * dot(grad3[gi2], x2, y2);
    }
    // Add contributions from each corner to get the final noise value.
    // The result is scaled to return values in the interval [-1,1].
    return 70.0 * (n0 + n1 + n2);
  }

  // 3D simplex noise
  public double noise(double xin, double yin, double zin) {
    double n0, n1, n2, n3; // Noise contributions from the four corners
    // Skew the input space to determine which simplex cell we're in
    double s = (xin + yin + zin) * F3; // Very nice and simple skew factor for 3D
    int i = fastfloor(xin + s);
    int j = fastfloor(yin + s);
    int k = fastfloor(zin + s);
    double t = (i + j + k) * G3;
    double X0 = i - t; // Unskew the cell origin back to (x,y,z) space
    double Y0 = j - t;
    double Z0 = k - t;
    double x0 = xin - X0; // The x,y,z distances from the cell origin
    double y0 = yin - Y0;
    double z0 = zin - Z0;
    // For the 3D case, the simplex shape is a slightly irregular tetrahedron.
    // Determine which simplex we are in.
    int i1, j1, k1; // Offsets for second corner of simplex in (i,j,k) coords
    int i2, j2, k2; // Offsets for third corner of simplex in (i,j,k) coords
    if (x0 >= y0) {
      if (y0 >= z0) {
        i1 = 1;
        j1 = 0;
        k1 = 0;
        i2 = 1;
        j2 = 1;
        k2 = 0;
      } // X Y Z order
      else if (x0 >= z0) {
        i1 = 1;
        j1 = 0;
        k1 = 0;
        i2 = 1;
        j2 = 0;
        k2 = 1;
      } // X Z Y order
      else {
        i1 = 0;
        j1 = 0;
        k1 = 1;
        i2 = 1;
        j2 = 0;
        k2 = 1;
      } // Z X Y order
    } else { // x0<y0
      if (y0 < z0) {
        i1 = 0;
        j1 = 0;
        k1 = 1;
        i2 = 0;
        j2 = 1;
        k2 = 1;
      } // Z Y X order
      else if (x0 < z0) {
        i1 = 0;
        j1 = 1;
        k1 = 0;
        i2 = 0;
        j2 = 1;
        k2 = 1;
      } // Y Z X order
      else {
        i1 = 0;
        j1 = 1;
        k1 = 0;
        i2 = 1;
        j2 = 1;
        k2 = 0;
      } // Y X Z order
    }
    // A step of (1,0,0) in (i,j,k) means a step of (1-c,-c,-c) in (x,y,z),
    // a step of (0,1,0) in (i,j,k) means a step of (-c,1-c,-c) in (x,y,z), and
    // a step of (0,0,1) in (i,j,k) means a step of (-c,-c,1-c) in (x,y,z), where
    // c = 1/6.
    double x1 = x0 - i1 + G3; // Offsets for second corner in (x,y,z) coords
    double y1 = y0 - j1 + G3;
    double z1 = z0 - k1 + G3;
    double x2 = x0 - i2 + 2.0 * G3; // Offsets for third corner in (x,y,z) coords
    double y2 = y0 - j2 + 2.0 * G3;
    double z2 = z0 - k2 + 2.0 * G3;
    double x3 = x0 - 1.0 + 3.0 * G3; // Offsets for last corner in (x,y,z) coords
    double y3 = y0 - 1.0 + 3.0 * G3;
    double z3 = z0 - 1.0 + 3.0 * G3;
    // Work out the hashed gradient indices of the four simplex corners
    int ii = i & 255;
    int jj = j & 255;
    int kk = k & 255;
    int gi0 = variatedPermutationTable[ii + doubledPermutationTable[jj + doubledPermutationTable[kk]]];
    int gi1 = variatedPermutationTable[ii + i1 + doubledPermutationTable[jj + j1 + doubledPermutationTable[kk + k1]]];
    int gi2 = variatedPermutationTable[ii + i2 + doubledPermutationTable[jj + j2 + doubledPermutationTable[kk + k2]]];
    int gi3 = variatedPermutationTable[ii + 1 + doubledPermutationTable[jj + 1 + doubledPermutationTable[kk + 1]]];
    // Calculate the contribution from the four corners
    double t0 = 0.6 - x0 * x0 - y0 * y0 - z0 * z0;
    if (t0 < 0) {
      n0 = 0.0;
    } else {
      t0 *= t0;
      n0 = t0 * t0 * dot(grad3[gi0], x0, y0, z0);
    }
    double t1 = 0.6 - x1 * x1 - y1 * y1 - z1 * z1;
    if (t1 < 0) {
      n1 = 0.0;
    } else {
      t1 *= t1;
      n1 = t1 * t1 * dot(grad3[gi1], x1, y1, z1);
    }
    double t2 = 0.6 - x2 * x2 - y2 * y2 - z2 * z2;
    if (t2 < 0) {
      n2 = 0.0;
    } else {
      t2 *= t2;
      n2 = t2 * t2 * dot(grad3[gi2], x2, y2, z2);
    }
    double t3 = 0.6 - x3 * x3 - y3 * y3 - z3 * z3;
    if (t3 < 0) {
      n3 = 0.0;
    } else {
      t3 *= t3;
      n3 = t3 * t3 * dot(grad3[gi3], x3, y3, z3);
    }
    // Add contributions from each corner to get the final noise value.
    // The result is scaled to stay just inside [-1,1]
    return 32.0 * (n0 + n1 + n2 + n3);
  }

  // 4D simplex noise, better simplex rank ordering method 2012-03-09
  public double noise(double x, double y, double z, double w) {

    double n0, n1, n2, n3, n4; // Noise contributions from the five corners
    // Skew the (x,y,z,w) space to determine which cell of 24 simplices we're in
    double s = (x + y + z + w) * F4; // Factor for 4D skewing
    int i = fastfloor(x + s);
    int j = fastfloor(y + s);
    int k = fastfloor(z + s);
    int l = fastfloor(w + s);
    double t = (i + j + k + l) * G4; // Factor for 4D unskewing
    double X0 = i - t; // Unskew the cell origin back to (x,y,z,w) space
    double Y0 = j - t;
    double Z0 = k - t;
    double W0 = l - t;
    double x0 = x - X0;  // The x,y,z,w distances from the cell origin
    double y0 = y - Y0;
    double z0 = z - Z0;
    double w0 = w - W0;
    // For the 4D case, the simplex is a 4D shape I won't even try to describe.
    // To find out which of the 24 possible simplices we're in, we need to
    // determine the magnitude ordering of x0, y0, z0 and w0.
    // Six pair-wise comparisons are performed between each possible pair
    // of the four coordinates, and the results are used to rank the numbers.
    int rankx = 0;
    int ranky = 0;
    int rankz = 0;
    int rankw = 0;
    if (x0 > y0) {
      rankx++;
    } else {
      ranky++;
    }
    if (x0 > z0) {
      rankx++;
    } else {
      rankz++;
    }
    if (x0 > w0) {
      rankx++;
    } else {
      rankw++;
    }
    if (y0 > z0) {
      ranky++;
    } else {
      rankz++;
    }
    if (y0 > w0) {
      ranky++;
    } else {
      rankw++;
    }
    if (z0 > w0) {
      rankz++;
    } else {
      rankw++;
    }
    int i1, j1, k1, l1; // The integer offsets for the second simplex corner
    int i2, j2, k2, l2; // The integer offsets for the third simplex corner
    int i3, j3, k3, l3; // The integer offsets for the fourth simplex corner
    // simplex[c] is a 4-vector with the numbers 0, 1, 2 and 3 in some order.
    // Many values of c will never occur, since e.g. x>y>z>w makes x<z, y<w and x<w
    // impossible. Only the 24 indices which have non-zero entries make any sense.
    // We use a thresholding to set the coordinates in turn from the largest magnitude.
    // Rank 3 denotes the largest coordinate.
    i1 = rankx >= 3 ? 1 : 0;
    j1 = ranky >= 3 ? 1 : 0;
    k1 = rankz >= 3 ? 1 : 0;
    l1 = rankw >= 3 ? 1 : 0;
    // Rank 2 denotes the second largest coordinate.
    i2 = rankx >= 2 ? 1 : 0;
    j2 = ranky >= 2 ? 1 : 0;
    k2 = rankz >= 2 ? 1 : 0;
    l2 = rankw >= 2 ? 1 : 0;
    // Rank 1 denotes the second smallest coordinate.
    i3 = rankx >= 1 ? 1 : 0;
    j3 = ranky >= 1 ? 1 : 0;
    k3 = rankz >= 1 ? 1 : 0;
    l3 = rankw >= 1 ? 1 : 0;
    // The fifth corner has all coordinate offsets = 1, so no need to compute that.
    double x1 = x0 - i1 + G4; // Offsets for second corner in (x,y,z,w) coords
    double y1 = y0 - j1 + G4;
    double z1 = z0 - k1 + G4;
    double w1 = w0 - l1 + G4;
    double x2 = x0 - i2 + 2.0 * G4; // Offsets for third corner in (x,y,z,w) coords
    double y2 = y0 - j2 + 2.0 * G4;
    double z2 = z0 - k2 + 2.0 * G4;
    double w2 = w0 - l2 + 2.0 * G4;
    double x3 = x0 - i3 + 3.0 * G4; // Offsets for fourth corner in (x,y,z,w) coords
    double y3 = y0 - j3 + 3.0 * G4;
    double z3 = z0 - k3 + 3.0 * G4;
    double w3 = w0 - l3 + 3.0 * G4;
    double x4 = x0 - 1.0 + 4.0 * G4; // Offsets for last corner in (x,y,z,w) coords
    double y4 = y0 - 1.0 + 4.0 * G4;
    double z4 = z0 - 1.0 + 4.0 * G4;
    double w4 = w0 - 1.0 + 4.0 * G4;
    // Work out the hashed gradient indices of the five simplex corners
    int ii = i & 255;
    int jj = j & 255;
    int kk = k & 255;
    int ll = l & 255;
    int gi0 = doubledPermutationTable[ii + doubledPermutationTable[jj + doubledPermutationTable[kk + doubledPermutationTable[ll]]]] % 32;
    int gi1 = doubledPermutationTable[ii + i1 + doubledPermutationTable[jj + j1 + doubledPermutationTable[kk + k1 + doubledPermutationTable[ll + l1]]]] % 32;
    int gi2 = doubledPermutationTable[ii + i2 + doubledPermutationTable[jj + j2 + doubledPermutationTable[kk + k2 + doubledPermutationTable[ll + l2]]]] % 32;
    int gi3 = doubledPermutationTable[ii + i3 + doubledPermutationTable[jj + j3 + doubledPermutationTable[kk + k3 + doubledPermutationTable[ll + l3]]]] % 32;
    int gi4 = doubledPermutationTable[ii + 1 + doubledPermutationTable[jj + 1 + doubledPermutationTable[kk + 1 + doubledPermutationTable[ll + 1]]]] % 32;
    // Calculate the contribution from the five corners
    double t0 = 0.6 - x0 * x0 - y0 * y0 - z0 * z0 - w0 * w0;
    if (t0 < 0) {
      n0 = 0.0;
    } else {
      t0 *= t0;
      n0 = t0 * t0 * dot(grad4[gi0], x0, y0, z0, w0);
    }
    double t1 = 0.6 - x1 * x1 - y1 * y1 - z1 * z1 - w1 * w1;
    if (t1 < 0) {
      n1 = 0.0;
    } else {
      t1 *= t1;
      n1 = t1 * t1 * dot(grad4[gi1], x1, y1, z1, w1);
    }
    double t2 = 0.6 - x2 * x2 - y2 * y2 - z2 * z2 - w2 * w2;
    if (t2 < 0) {
      n2 = 0.0;
    } else {
      t2 *= t2;
      n2 = t2 * t2 * dot(grad4[gi2], x2, y2, z2, w2);
    }
    double t3 = 0.6 - x3 * x3 - y3 * y3 - z3 * z3 - w3 * w3;
    if (t3 < 0) {
      n3 = 0.0;
    } else {
      t3 *= t3;
      n3 = t3 * t3 * dot(grad4[gi3], x3, y3, z3, w3);
    }
    double t4 = 0.6 - x4 * x4 - y4 * y4 - z4 * z4 - w4 * w4;
    if (t4 < 0) {
      n4 = 0.0;
    } else {
      t4 *= t4;
      n4 = t4 * t4 * dot(grad4[gi4], x4, y4, z4, w4);
    }
    // Sum up and scale the result to cover the range [-1,1]
    return 27.0 * (n0 + n1 + n2 + n3 + n4);
  }

  // Inner class to speed upp gradient computations
  // (array access is a lot slower than member access)
  private static class Grad {

    double x, y, z, w;

    Grad(double x, double y, double z) {
      this.x = x;
      this.y = y;
      this.z = z;
    }

    Grad(double x, double y, double z, double w) {
      this.x = x;
      this.y = y;
      this.z = z;
      this.w = w;
    }
  }
}
